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Guiding Customers on Their Journeys

Guiding Customers on Their Journeys

Guiding Customers on Their Journeys

How AI can assist agents assist customers.

Businesses with contact center operations are facing a core challenge. Namely customers’ service expectations keep rising, but the agents whose job it is to keep them happy often lack the right tools, resources, and training to serve them well.

One recent survey found that 83% of support teams are seeing customer expectations increase in 2023 compared to 75% a year earlier. But just 40% of respondents said they were confident in meeting those expectations.

Breakdowns between customer expectations and contact centers’ abilities to deliver occur in several ways.

  • Customers get placed on long holds while agents search for information or escalate calls to managers.
  • The explosion of channels that customers use to contact businesses has added another layer of complexity and potential for frustration.

Businesses, then, need to be set up to respond to customers in a seamless way in whatever channel they choose.

At the same time, contact centers are struggling to monitor and improve agent performance. The post-COVID-19 pandemic reality of remote contact center teams has made monitoring and supporting staff exponentially more difficult for managers. They can no longer walk the floor to respond to a raised hand. They can’t sit next to an agent and coach them through a call.

AI: An Essential Agent and Manager Assistant

There may be no magic bullet to resolve these complex challenges, but artificial intelligence (AI) technology has emerged as a powerful - I would argue essential - tool that can transform both the customer and agent experience for the better. One that can give businesses valuable new insights into their customer service.

Today’s customers don’t want to be put on hold for long periods of time or repeatedly transferred from one agent to another. They also want to contact a business across numerous touchpoints - social media, email, telephone - and not have to repeat their request each time.

Businesses...need to be set up to respond to customers in a seamless way in whatever channel they choose.

AI can effectively plug agents directly into a business’s knowledge base, putting all of a customer’s information at their fingertips regardless of which channel they’re using. That feature also enables it to give agents real-time assists during the call, prompting them with relevant information based on the caller’s queries.

With AI applied in this way, there are no more 15-minute holds while the agents go searching through account information or other documentation or seeks advice from a supervisor.

Perhaps counterintuitively, AI is proving to be an invaluable way to improve the emotional side of customer care.

AI sentiment tracking can alert agents when a customer is showing signs of frustration, prompting them to slow down, or provide them with ideas for taking a different approach, including bringing in a supervisor immediately.

AI can also allow agents to connect customers with complex cases to actual experts within the organization who can resolve their issues more effectively than the customer care team.

The end result is better customer-care metrics: lower levels of call abandonment, higher FCR, and higher overall customer satisfaction.

Leveraging AI to achieve these results is crucial because the value to businesses in providing excellent customer service has perhaps never been higher.

Some 72% of consumers say they’re willing to spend more with a company that offers high-quality customer service, according to one survey. And 94% of consumers are more likely to make further purchases from a company after a positive customer service experience.

Happier Agents, Happier Customers

Another vital industry metric that AI can improve is agent job satisfaction: something that is intimately linked to customer satisfaction.

The happier and more empowered agents are in their work, the greater their likelihood of staying with that employer, and the better they can provide excellent service to customers.

Perhaps counterintuitively, AI is proving to be an invaluable way to improve the emotional side of customer care.

Any fears of agent longevity costing companies more through pay raises are offset by reduced hiring and training costs, and, more critically, by greater customer loyalty, likelihood of referrals, and ultimately more revenue opportunities.

The average customer service repre- sentative between 20 and 34 years old stays in their role for just over one year (Harvard Business Review). The average contact center turnover rate is as high as 45%—twice as high as other depart- ments. More than 70% of customer service agents surveyed last year said they had considered quitting.

Customer service agents quit because they feel they are unable to meet the needs of the people they speak with every day. When agents are under-resourced, it can result in frustrated and angry customers. This can, in turn, cause agents to feel demotivated and burned out.

On the flip side, agents equipped with the tools and support they need can deal with queries, get a sense of satisfaction, and delight customers (or at the very least reduce their frustration). This creates a virtuous circle in which agents are happier and able to perform better in their jobs.

The best AI solutions provide agents with an easy-to-use interface that contains records of interactions between the company and the customer, regardless of the channel they have come through.

This enables agents to access the full range of information they need in real time, saving them from frustrating manual tasks like reading through product manuals. Or searching for information that might reside in a dark corner of a CRM application.

The AI tools can answer questions like:

  • Who is best to contact for questions about billing, finance, or engineering?
  • Which of them are available now?

These details need to be natively available through an interface that doesn’t require months of training to use.

If agents have to navigate a dozen tabs to access multiple applications to deal with queries all day, they will get burned out. A well-designed and accessible AI-powered interface isn’t a nice-to-have; it’s increasingly a must-have.

Leveling the Playing Field

Chatbots, of the kind popularized by OpenAI’s ChatGPT, can pull answers from huge swaths of information using natural-language queries, reducing the technical demands of the job and allowing agents to focus on the human side of their role: connecting with customers.

Recent — and fascinating — research shows that the least skilled staff often benefit most from the use of AI assistants.

AI platforms can now provide CSAT scores from 100% of callers: without any additional action from them.

A U.S. study in May 2023 discovered that customer service agents at an unnamed large firm worked 14% faster on average while using an AI assistant, while the most skilled employees showed little across-the-board improvement.

We have all come across colleagues who are personable and have great rapport with clients but who struggle to get across the technical stuff. The right tools can level the playing field when it comes to technical ability and bring more of those people into our organizations.

A Revolution in CSAT Monitoring

As well as alerting managers to interactions that are going south in real time, AI sentiment analysis also allows for the production of CSAT scores for every call. This is a huge step up from the traditional reliance on post-call surveys, which we all know is a very patchy tool that tends only to reflect the most extreme CSAT outcomes.

AI platforms can now provide CSAT scores from 100% of callers: without any additional action required from them.

This gives businesses access to a whole new level of insights into how their customers feel and how to better address their pain points. This helps managers focus team training on relevant aspects of customer care and zero in on individual agents who need more support and coaching. It provides managers with a metric through which to give out praise and even create healthy competition.

Many customer agents get monthly or quarterly ratings via an algorithm that they, and often their manager, don’t understand, which relates to interactions they have long forgotten. Immediate CSAT scores help agents feel rewarded and allow them to track their progress.

As this article makes clear, AI isn’t just delivering marginal gains to businesses’ contact center operations. It represents a true paradigm shift in the way they can attain better, real-time insights into customer needs and faster, more targeted support for agents.

The intelligent application of AI will increasingly differentiate successful customer service operations from those that struggle to meet rising customer expectations.

Solving the Remote Work Coaching Challenge

AI is also enabling businesses to reap the benefits of remote contact center operations, while overcoming many of the challenges it has created.

Remote work has allowed them to widen the talent pool from which they can hire. Companies no longer need to find hundreds of customer service staff that live within a few miles of a single building. People previously shut out of the workforce because of location or unavailability for full-time work can now plug-in from home to do shifts at times that better suit them.

Even in an office environment, a contact center manager can’t expect to stay on top of everything that’s going on within their team. Instead, they have had to rely on ad hoc performance checks, patchy customer feedback, and staff seeking them out for help.

With the advent of AI, managers also now have access to tools that help them know where to focus their attention and how to get more out of their time with staff. AI can effectively act as a 24/7 coach, enabling organizations to reduce costs and better target their training.

AI sentiment monitoring, for example, can analyze customer satisfaction levels and flag if customers are getting frustrated or annoyed. Managers can respond to that data and communicate with agents while they are still on the call or, if necessary, take over.

AI can deliver call summaries and action items to show how closely agents have stuck to the script and ensure they complete follow-ups. Transcripts and summaries make it faster to evaluate calls and drill down on what could be improved. Coaching can be directed towards those who need it most and tailored to what will best help them.

These new capabilities are just as effective if employees are clustered together in one room or dispersed across a country or continent.

Brian Peterson

Brian Peterson

Brian Peterson is a co-founder and the Chief Technology Officer at Dialpad. Previously, he was a Senior Software Engineer at Google, building the front end of Google Voice.

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